Lauric Alexandra, Ludwig Calvin G, Malek Adel M
Cerebrovascular and Endovascular Division and Cerebrovascular Hemodynamics Laboratory, Department of Neurosurgery, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts, USA.
Cerebrovascular and Endovascular Division and Cerebrovascular Hemodynamics Laboratory, Department of Neurosurgery, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts, USA.
World Neurosurg. 2022 Mar;159:e8-e22. doi: 10.1016/j.wneu.2021.11.038. Epub 2021 Nov 23.
Radiomics is a powerful tool for automatic extraction of morphological features, but when applied to cerebral aneurysms, it is inferior to established descriptors in classifying rupture status. We sought a strategy to recover neck orientation and parent vessel caliber to enhance Radiomics performance and facilitate its adoption for aneurysm risk stratification.
We analyzed 135 sidewall (32 ruptured) and 216 bifurcation (90 ruptured) aneurysms from three-dimensional rotational catheter angiography datasets. Clinical three-dimensional rotational catheter angiography defined in arbitrary orientation underwent affine transformations enabling aneurysm neck alignment to XY plane before analysis in PyRadiomics, facilitating automatic extraction of aneurysm height and width, previously not possible with random alignment. Additionally, parent vessel size was estimated from aneurysm location and incorporated into enhanced Radiomics (height, width, height/width, size ratio). Rupture status classification was compared across methodologies for 31 automatically computed conventional Radiomics, enhanced Radiomics, and established size/shape descriptors using univariate, multivariate, and area under the curve (AUC) statistics.
Enhanced Radiomics-derived height/width and size ratio were significantly higher in both ruptured subsets. Using multivariate analysis in sidewall lesions, enhanced Radiomics (AUC = 0.85) matched established features (AUC = 0.86) and outperformed conventional Radiomics (AUC = 0.82); in bifurcation lesions, enhanced Radiomics (AUC = 0.78) outperformed both established features (AUC = 0.76) and conventional Radiomics (AUC = 0.74).
Enhanced Radiomics incorporating neck orientation and parent vessel estimate is an efficient operator-independent methodology that offers superior rupture status classification for both sidewall and bifurcation aneurysms and should be considered a strong candidate for larger-scale multicenter and multimodality validation.
放射组学是一种用于自动提取形态特征的强大工具，但应用于脑动脉瘤时，在对破裂状态进行分类方面不如既定的描述符。我们寻求一种策略来恢复瘤颈方向和载瘤动脉管径，以提高放射组学性能，并促进其用于动脉瘤风险分层。
我们分析了来自三维旋转导管血管造影数据集的135个侧壁动脉瘤（32个破裂）和216个分叉动脉瘤（90个破裂）。对以任意方向定义的临床三维旋转导管血管造影进行仿射变换，使动脉瘤瘤颈在PyRadiomics分析前与XY平面对齐，便于自动提取动脉瘤的高度和宽度，这在随机对齐时是无法做到的。此外，根据动脉瘤位置估计载瘤动脉大小，并将其纳入增强放射组学（高度、宽度、高宽比、大小比）。使用单变量、多变量和曲线下面积（AUC）统计，比较了31种自动计算的传统放射组学、增强放射组学和既定的大小/形状描述符在不同方法下的破裂状态分类。
在两个破裂亚组中，增强放射组学得出的高宽比和大小比均显著更高。在侧壁病变的多变量分析中，增强放射组学（AUC = 0.85）与既定特征（AUC = 0.86）相当，且优于传统放射组学（AUC = 0.82）；在分叉病变中，增强放射组学（AUC = 0.78）优于既定特征（AUC = 0.76）和传统放射组学（AUC = 0.74）。
结合瘤颈方向和载瘤动脉估计的增强放射组学是一种高效的、与操作者无关的方法，对侧壁和分叉动脉瘤均能提供更好的破裂状态分类，应被视为大规模多中心和多模态验证的有力候选方法。
Zotero 插件